/knowledge
What I learned, and keep learning.
Thorough, first-principles explainers of the data science I studied at the University of Melbourne — and the topics I taught. Writing each one from scratch is how I keep the fundamentals sharp. Built one topic at a time; 1 live so far.
Natural Language ProcessingTokens, TF-IDF, embeddings, transformers
COMP90042Live
Statistical Machine LearningBias-variance, regularisation, generalisation
Master'sNext
Bayesian StatisticsPriors, posteriors, MCMC
Master'sPlanned
Cluster & Cloud ComputingMPI, Spark, HPC at scale
COMP90024Planned
Linear AlgebraVectors, eigenvalues, the SVD
Bachelor'sPlanned
Linear Statistical ModelsOLS, inference, diagnostics
Bachelor'sPlanned
Database SystemsRelational model, SQL, indexing
Bachelor'sPlanned
Artificial IntelligenceSearch, logic, planning
Bachelor'sPlanned